data envelopment analysis (dea) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. it is based on solving linear programming problems. since 1978 when basic dea model was introduced many its modifications were formulated. among them are two or multi-stage models with serial or parallel structure often called net...

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there ar...

in this article, non radial method of dynamic dea with the parallel network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. in this model, dmu divisions under evaluation have been put together in parallel. but its dynamic structure is assumed in series. since in real applications there are undesirable inputs and o...

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can ...

The correlated models are introduced in this article regarding revenue efficiency and profit efficiency in dynamic network production systems. The proposed models are not only applicable in measuring efficiency of divisional, periodical and overall efficiencies, but recognizing the exact sources of inefficiency with respect to revenue and profit efficiencies. Two numerical examples, consisting ...

  In this article, Non radial method of dynamic DEA with the parallel network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. In this model, DMU divisions under evaluation have been put together in parallel. But its dynamic structure is assumed in series. Since in real applications there are undesirable inputs an...

We propose a dynamic DEA model involving network structure in each period within the framework of a slacks-based measure approach. We have previously published the network SBM (NSBM) and the dynamic SBM (DSBM) models separately. Hence, this article is a composite of these two models. Vertically, we deal with multiple divisions connected by links of network structure within each period and, hori...

We examine the distribution of incentives across executives with explicit divisional responsibilities, those with broad oversight authority over the firm, and CEOs. Oversight executives have pay-performance incentives that are $1.22 per thousand dollar increase in shareholder wealth higher than those of divisional executives. For CEOs, incentives are $5.65 per thousand higher than for executive...

In Chen, Cook, Kao, and Zhu (2013), it is demonstrated, as a network DEA pitfall, that while the multiplier and envelopment DEA models are dual models and equivalent under the standard DEA, such is not necessarily true for the two types of network DEAmodels in deriving divisional efficiency scores and frontier projections. As a reaction to this work, we demonstrate that the duality in the stand...

In this paper we look at the effect of CEO turnover on the divisional investment of multi-divisional firms. We predict that after CEO turnover, new CEOs will use different divisional investment policy and internal capital allocation to realize strategy reorientation, improve firm performance or make more entrenchment. Furthermore, by looking at new CEO’s divisional preference at preand post-tur...